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interpret science as imperfect knowledge and emphasise the evolution of scientifi c knowledge during learning as shaped by individual, social and cultural factors. The theoretical background of the approach comes part-ly from the post-positivist philosophy of science, the work of Lakatos (1970) and Popper (1972), according to which knowledge is not ‘dis-cover ed’ but rather ‘construed’ by a community of like-minded people.
Another important theoretical foundation is the research in cognitive psychology aiming to characterise conceptual development. In order to understand the current goals of science education and our recommenda-tions concerning the teaching of scientifi c knowledge, we summarise briefl y the results of psychological and education theoretical research on the organisation of knowledge and conceptual development.
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process of perception (e.g., visual, acoustic images, basic and complex images formed by the perception of different smells, tastes, pain, heat, body position and space). These mental images are not simply imprints of the external world; they are, instead, constructed and reconstructed from their elements and fi lled in with our conceptual knowledge as they are used or evoked.
The other type of representation is digital, where the original object and its mental representation are not alike, as the perceived stimulus is converted into a different symbol system, a linguistic code. Linguistic signs or symbols are assigned to the original visual image, sound, taste, etc., and propositions are constructed. Propositions are statements of fact showing the relationship between two concepts (e.g., the rose is a plant).
Propositional representations capture the ideational content of the mind.
They are language-like but not words, they are discrete, refer to indi-vidual objects, and abstract (may represent information from any modal-ity), i.e., they constitute a modality-independent mental language. This class of knowledge is a system of verbal information or conceptual knowledge.
According to the classic interpretation of mental representation, the symbol processing paradigm, the process of representation involves the manipulation of symbols according to certain rules. There are now other models of knowledge representation in cognitive science. The most widely recognised theory relies on a connectionist model of information processing and posits distributed representations, which are composed of units below the level of symbols, i.e., are sub-symbolic. The theory maintains that the exceptional speed and fl exibility of information man-agement are explained by the distributed storage of information as a pattern of activation within the same network. Several researchers share the view that distributed representations describe the microstructure of cognitive representations, while the symbolic theory describes its macro-structure (McClelland, Rumelhart, & Hinton, 1986, cited in Eysenck &
Keane, 1990, p. 260). As cognitive pedagogy and the research on con-ceptual development focus mainly on the macro-level, which is captured by the symbol processing approach, the theoretical framework described below details this approach.
Our knowledge system is thus composed of two different knowledge entities, images and concepts, with a network of transient or longer-term
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connections between these knowledge entities, which are created as a result of learning and reasoning. This network may have sections of structures of varied complexity constructed from various elements. If we look at a clearly defi ned topic, we may observe a hierarchical order in the structuring of concepts, but further complicated associations and links may form between distant concepts during the interpretation of a task or situation (Mérő, 2001). The size and the quality of our knowledge system are indicated by the number of units in the knowledge network and by the richness of connections. Our knowledge is continuously shaped, new elements are built in and new connections are constructed between existing elements as new associations are discovered throughout our lives. Our knowledge system varies by knowledge areas: it is richly structured in areas where we have a body of knowledge accumulated and polished through several years of varied experiences, and it is poorly structured in areas that we only have superfi cial experience of or where the knowledge acquired sometime in the past has not been recalled for a long time.
Concept Formation and the Organisation of Concepts
A concept is a category that allows entities forming a class in some way to be treated as a single unit of thought. In the system of József Nagy (1985, p. 153), a concept is a collection of elementary ideas representing a certain object. Since an object is defi ned by its properties, both of the object itself and its properties are represented by symbols. The symbol referring to the object is a name, while the symbol referring to the prop-erty is a feature. A name-feature association corresponding to a given object-property association may become an idea if the properties of prop-erties are assigned features and/or we have an image of these propprop-erties (Nagy, 1985, p. 164). This is how an elementary concept is formed. As the next step of concept ontogenesis, further features are added, an elemen-tary concept becomes a simple concept, and the object may be catego-rised, i.e., it can be decided whether the object is an exemplar of a given conceptual category or not on the basis of its features. When a concept becomes embedded in a conceptual hierarchy defi ned by certain condi-tions, it becomes a complex concept. General concepts that are relevant
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to life (e.g., matter, living organisms, society) may be developed into a complex concept by organising individual complex concepts of relevant objects constructed from different perspectives into a unifi ed system. In this view, therefore, the development of the conceptual system is charac-terised by gradual enrichment and structuring.
Systematic education theoretical research on concept formation began in the 1970s building on the frameworks of philosophy and classic logi-cal logi-calculus, and making use of the achievements of semiotics. The main emphasis was fi rst on the acquisition of the features of conceptual cate-gories, generalisation within a category, the differentiation of categories and the structuring of the conceptual system (Bruner, 1960; Vojsvillo, 1978). In parallel with these efforts another approach emerged, which maintains that a concept not only refl ects reality and the essence of a given entity but it is a knowledge component under constant develop-ment both in content and in its embeddedness in the conceptual system, which is in the service of certain psychic functions (Nagy, 1985).
Over the past three decades, research in cognitive psychology and developmental psychology has added several details to early theories in areas such as the process of categorisation, the mental representation of categories, the role of mental representation in behaviour and in the pre-diction of future behaviour, and the neurobiological and neuropsycho-logical aspects of perceptual categorisation (Kovács, 2003; Murphy, 2002; Ragó, 2000; 2007a; 2007b). The results indicate that category boundaries are not always unambiguous or strictly defi ned, a character-istic that became known as ‘fuzziness’ in the literature. The features characterising a conceptual category and the exemplars of that category may be more or less typical, and a given object may even be an exemplar of several different categories depending on the context and the actual task or purpose. Concepts are therefore not simply retrieved from the conceptual network, but are constructed anew based on the stored prop-erties as required by the given situation. Several concepts (mostly ab-stract concepts) are formed by creating a prototype on the basis of ex-perien ces rather than by learning the features characterizing the category.
At a perceptual level, categorisation is already operative in infants but the identifi cation of the features defi ning a category and the method of categorization undergo substantial changes during the course of cogni-tive development. The initial broad categories are narrowed down and
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divided into further categories while the features defi ning a category are replaced by others (Ragó, 2000).
Categorisation constitutes the foundations of the development of more complex conceptual systems. We would not be able to cope in everyday life without creating schemas based on our previous experiences to repre-sent events, situations, ideas, relations and objects. A cognitive schema is a general knowledge structure applicable in a specifi c situation, a complex conceptual system, a culture-dependent unit of thought with a character-istic structure that is meaningful in itself. Schemas control or infl uence the perception and interpretation of different state-of-affairs, events and situations (Bartlett, 1932) while at the same time they are continuously modifi ed as the new information is processed. Schemas interact with each other, are organised dynamically and form larger units (e.g., scripts, memory packages, semantic memory units) (Baddeley, 1997). It is cogni-tive schemas that organise our memory traces into thought. Only those memory traces play a role in our thinking which are linked to our exist-ing cognitive schemas (Mérő, 2001, p. 175) and we only perceive what fi ts into our existing schemas.
The quality and level of organisation of knowledge systems vary be-tween individuals and constantly change and evolve within any given individual. In cognitive psychology research the structure of simple hi-erarchical conceptual systems is explored through verifi cation tasks (where the subject is asked to verify the truth of statements refl ecting the conceptual hierarchy under investigation) and the structure of schemas is analysed through tasks involving the interpretation and recall of situa-tions and texts. In education theoretic research, one of the most common methods of exploring knowledge and beliefs is based on clinical inter-views as developed by Piaget (1929). Piaget originally interviewed young children to fi nd out what kind of knowledge and beliefs underlay their answers when they gave an explanation for one or another phenom-enon in the world. Besides the interview method, open-ended question tasks are also commonly used where students are asked to give a scien-tifi c explanation for various phenomena based on their everyday experi-ences. The level of interpretation of a given phenomenon can be deter-mined by analysing and classifying the content of the answers, and com-prehension problems and diffi culties can be identifi ed (Korom, 2002).
The system of concepts stored in memory and the network of
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tions can be visualised with the help of various concept-mapping tech-niques, which may also assist the acquisition of new knowledge (Habók, 2007; Nagy, 2005; Novak, 1990).